applications

Approaching the Harm of Gradient Attacks While Only Flipping Labels

arXiv:2503.00140v3 Announce Type: replace-cross Abstract: Machine learning systems deployed in distributed or federated environments are highly susceptible to adversarial manipulations, particularly a

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AtomicVLA: Unlocking the Potential of Atomic Skill Learning in Robots

DGX agent

arXiv:2603.07648v2 Announce Type: replace-cross Abstract: Recent advances in Visual-Language-Action (VLA) models have shown promising potential for robotic manipulation tasks. However, real-world robo

applicationsarxiv-cs-cv

9 Sept 2026

BiDexGrasp: Coordinated Bimanual Dexterous Grasps across Object Geometries and Sizes

arXiv:2604.06589v2 Announce Type: replace Abstract: Bimanual dexterous grasping is a fundamental and promising area in robotics, yet its progress is constrained by the lack of comprehensive datasets a

CLUES-WEASEL: No additional clues required to choose your time series clustering algorithm

arXiv:2609.07606v1 Announce Type: new Abstract: Time series data is very common in many real-world applications and in numerous domains, with increasing interest for automated information extraction u

ContactWorld: What Representations Matter in Vision-Tactile World Models for Contact-Rich Manipulation

arXiv:2606.13877v2 Announce Type: replace Abstract: Contact-rich manipulation requires world models to capture complex interaction dynamics from heterogeneous visual and tactile observations, yet the

Context-Aware System Synthesis, Task Assignment, and Routing

arXiv:1706.04580v3 Announce Type: replace Abstract: The design and organization of complex robotic systems traditionally requires laborious trial-and-error processes to ensure both hardware and softwa

ControlTac: Scaling Tactile Data with Physically Controlled Tactile Image Generation

arXiv:2505.20498v3 Announce Type: replace Abstract: Vision-based tactile sensing is widely used in perception, reconstruction, and robotic manipulation, yet collecting large-scale tactile data remains

Data Quality Rule Generation with LLMs

arXiv:2609.06053v1 Announce Type: new Abstract: The validation of data, such as customer and employee data, is an important task in many organizations. Errors in data can have severe consequences. For

Differentiable Causal Discovery for Singular Linear Models under Confounding

arXiv:2601.01368v2 Announce Type: replace Abstract: Score-based causal discovery in the presence of unobserved confounders requires both a consistent scoring criterion and an efficient search over gra

EdMCGS: Event-Driven Markov Chain Gaussian Splatting for Extreme-Low-Frame-Rate Dynamic Scene Reconstruction

arXiv:2609.08332v1 Announce Type: new Abstract: We present EdMCGS (Event-driven Markov chain Gaussian Splatting), an end-to-end method for reconstructing dynamic 3D scenes from extreme-low-frame-rate

EquiGQNet: Fast Grasp Quality Evaluation via Shared Equivariant Point Cloud Encoding

arXiv:2609.07145v1 Announce Type: new Abstract: Planning six-degree-of-freedom (6-DoF) grasps for unseen objects in cluttered tabletop scenes from a single-view depth image requires accurate and effic

Explainable Temporal Attention-based Defect Detection For Fillet Joints in Real-Time Gas Metal Arc Welding Based on Multi-modal Data

arXiv:2609.07893v1 Announce Type: cross Abstract: Deep learning is an efficient technique to monitor the real time welding process, reducing post-welding repairs and production delays. This paper leve

Fewer yet critical: Reducing Redundant Token Dependencies for Transformer-based Time Series Forecasting

arXiv:2503.06867v2 Announce Type: replace-cross Abstract: Time series forecasting (TSF) is important in real-world applications. Recently, Transformer-based methods have achieved strong performance by

FPicker: Topology-Guided Evolution for Filament Tracing in Low-SNR Microscopy

arXiv:2609.08305v1 Announce Type: new Abstract: Automating filament tracing in Cryo-Electron Microscopy (Cryo-EM) is essential for 3D helical reconstruction but challenged by intersecting topologies a

Functional-SLAM: Interaction-Aware Mapping with Online Functional Scene Graphs

arXiv:2609.07497v1 Announce Type: new Abstract: Existing SLAM systems lack modeling of the functional relations required for fine-grained robotic interaction. Functional 3D scene graphs can represent

GALoc: Gravity Aligned Wireframes for Depth-Free Monocular Floorplan Localization

arXiv:2609.08385v1 Announce Type: new Abstract: Floorplans are compact, appearance-invariant maps ideal for indoor localization, yet existing methods rely on depth networks that are brittle in clutter

General Robotics’ GRID platform engineers itself, cutting robot setup to hours

General Robotics Technology Inc. said today that its GRID robot intelligence platform now automates its own engineering work, cutting the time needed to get a new robot into production from about a mo

applicationssiliconangle

Generalizable 6D Pose Estimation of Textureless Objects with Planar-based Gaussian Splatting

arXiv:2609.07231v1 Announce Type: new Abstract: Estimating the 6D pose of textureless objects without prior CAD models remains a critical challenge due to the lack of appearance features. While recent

Granular-Ball Quantum Clustering for Resource-Efficient and Robust Learning

arXiv:2609.06016v1 Announce Type: new Abstract: Quantum clustering aims to exploit quantum feature representations to uncover complex data structures beyond conventional Euclidean geometry. Yet this s

Heat Field Signatures: From Point Clouds to Smooth Geometry

arXiv:2609.07975v1 Announce Type: new Abstract: Bringing multiscale geometric analysis directly to irregular point clouds remains difficult: quantities such as local dimension, anisotropy, density var

HoneyRoute: Honeypot-Model Routing for Adversarial LLM Serving

arXiv:2609.08306v1 Announce Type: cross Abstract: We introduce HoneyRoute, an inference-serving layer that detects whether an incoming request is malicious and, if so, routes it to a dedicated honeypo

HOPE: Heterophily-Aware Open-Set Node Classification with Pseudo-Extrapolation

arXiv:2609.08685v1 Announce Type: new Abstract: Standard open-set node classification methods rely on the homophily assumption, where connected nodes share labels. However, real-world graphs are often

IIns-VAE+: A Robust Transfer Learning Framework for Environmental Identification in Wireless Sensing

arXiv:2609.06131v1 Announce Type: cross Abstract: Environmental identification in wireless sensing is essential for 6G integrated sensing and communication (ISAC) systems to achieve reliable situation

Instance-wise Linearization of Neural Network for Model Interpretation

arXiv:2310.16295v2 Announce Type: replace-cross Abstract: Neural network have achieved remarkable successes in many scientific fields. However, the interpretability of the neural network model is stil

KODAMA: Multimodal Digital Twin Reconstruction for Urban RF Propagation Modelling

arXiv:2609.07298v1 Announce Type: new Abstract: 3D reconstruction typically strives for geometric fidelity or visual plausibility. Radio frequency digital twins (RFDT) are instead judged by whether co

Leveraging contextual events on structure-aware next activity prediction

arXiv:2609.08622v1 Announce Type: new Abstract: Predictive process monitoring aims at forecasting various aspects of running processes. Among the different tasks, next activity prediction represents t

LightSplat: Real-Time High-Fidelity 3D Gaussian SLAM with Loop Closure

arXiv:2609.07274v1 Announce Type: cross Abstract: SLAM systems based on 3D Gaussian Splatting (3DGS) have recently demonstrated promising reconstruction accuracy for dense 3D scene representations. Ho

Machine learning doesn't end when the model is trained. You still need to evaluate it, deploy it, and build the infrastructure to keep it wo…

applicationsfrancois-chollet--x

Machine learning doesn't end when the model is trained. You still need to evaluate it, deploy it, and build the infrastructure to keep it working in production. Today's Deal of the Day takes you acros

MSSP: Multi-Scale Spatially-Constrained Partition for Unsupervised Semantic Segmentation of 3D Point Clouds

arXiv:2609.06959v1 Announce Type: new Abstract: 3D point cloud semantic segmentation is essential for real-world spatial understanding, yet the prohibitive cost of human annotations motivates unsuperv

Multi-Task Learning for Sparsely-Labeled Time Series: A Case Study on Cold-Hardiness Modeling

arXiv:2609.09062v1 Announce Type: new Abstract: We present a real-world case study of multi-task learning (MTL) for temporal process modeling from limited data with temporally sparse labels. Specifica

Not Just Oversmoothing: Detecting the Echo Chamber Effect in Graph Neural Networks

arXiv:2609.06521v1 Announce Type: new Abstract: Oversmoothing is a well-known failure mode of Graph Neural Networks (GNNs). However, most existing diagnostics rely on global aggregation measures that

OmniNav: Robust Long-Horizon Target Navigation in Dynamic Environments

arXiv:2609.08159v1 Announce Type: new Abstract: Long-horizon target navigation requires a robot to sustain task execution across evolving observations, decisions, and physical interactions. This requi

OpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining

arXiv:2609.07398v1 Announce Type: new Abstract: World-Action Models inherit world knowledge from video-generative priors, and channel it into executable control signals through embodied experience. Ex

PAI-Actor: Cinematic Multi-Character Replacement in Dynamic Scenes

arXiv:2609.05918v1 Announce Type: new Abstract: We present PAI-Actor, a cinematic multi-character animation framework for character replacement in dynamic movie scenes. Unlike conventional animation s

PAN: A World Model for General, Actionable, and Long-Horizon World Simulation

arXiv:2511.09057v4 Announce Type: replace Abstract: A world model is a cognitive simulator of the real-world environment allowing biological agents to reason about how the world evolves, whether spont

Privacy Leakage from a Thousand Words: Millipixel Location Recovery from Dot Maps

arXiv:2609.07623v1 Announce Type: cross Abstract: Dot maps, which visualize individual data points as dots over a geographic region, are widely used across diverse domains to represent spatial pattern

REFINE: Trajectory Representation Learning via Closed-Loop Transcription -- Extended Version

arXiv:2609.07206v1 Announce Type: new Abstract: Trajectory representation learning underpins a wide range of trajectory analytics tasks; however, most existing self-supervised approaches, whether disc

Robust Decentralized Federated Distillation via Multi-Modality Knowledge Collaboration

arXiv:2609.07230v1 Announce Type: new Abstract: This paper propose a robust decentralized federated distillation method that enables clients with heterogeneous models to collaborate through prediction

Robust Optical Flow Computation: A Higher-Order Differential Approach

arXiv:2410.09563v2 Announce Type: replace Abstract: In the domain of computer vision, optical flow stands as a cornerstone for unraveling dynamic visual scenes. However, the challenge of accurately es

Sector-Mean: Deterministic Initialization of K-Means Centroids via Angular Sector Partitioning

arXiv:2609.06468v1 Announce Type: new Abstract: K-Means is one of the most widely used clustering algorithms, but its susceptibility to initial centroid selection remains a primary bottleneck for its

Sparse Incident-Cluster Learning for 12-hour Port Flood Pre-warning in Digital-Twin Analytics

arXiv:2609.06109v1 Announce Type: new Abstract: Port flood digital twins require analytics that warn operators before disruption, but official warning incidents are often few and adjacent observations

SpatialBlock: Enhancing Spatial Intelligence in LVLMs via Synthetic Block-Stacking Problem

arXiv:2609.07064v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) have achieved strong performance on diverse visual tasks, yet their ability to reconstruct and reason about the 3D

State-of-the-Art in Learning-by-Demonstration with Passive Observation for Industrial Assembly Automation

arXiv:2609.07165v1 Announce Type: new Abstract: Learning-by-Demonstration (LbD) enables intuitive robot programming by capturing expert skills, which is crucial for agility in high-mix, low- volume ma

Stochastically Perturbed Weights: Ensembles from Deterministic Machine-Learning Weather Models

arXiv:2609.08412v1 Announce Type: new Abstract: Machine-learning weather models (MLWMs) now match or outperform operational numerical weather prediction (NWP) at global medium-range forecasting, at fa

SWE-Tester: Training Open-Source LLMs for Issue Reproduction in Real-World Repositories

arXiv:2601.13713v2 Announce Type: replace-cross Abstract: Software testing is crucial for ensuring the correctness and reliability of software systems. Automated generation of issue reproduction tests

TANGO: Humanoid Navigation in Cluttered Environments with a Whole-Body Vision-Language-Action Model

arXiv:2609.09158v1 Announce Type: new Abstract: We study the problem of navigating cluttered indoor environments with a humanoid robot. Unlike conventional methods that model navigation as a 2D path p

Tensor network representations of discrete maximum entropy distributions via mean polytopes

arXiv:2609.07184v1 Announce Type: cross Abstract: We present tensor network representations for discrete maximum entropy distributions under expectation constraints. To this end, we introduce Computat

Toward Robust Single-Photon Perception for Robots: A Condition-Aware Active Learning Approach

arXiv:2505.04376v2 Announce Type: replace-cross Abstract: LiDAR-based perception plays a fundamental role in modern robotic systems for environment understanding and navigation. Single-photon LiDAR (S